An optimized hybrid methodology for short‐term traffic forecasting in telecommunication networks

M Alizadeh, MTH Beheshti… - Transactions on …, 2023 - Wiley Online Library
With the rapid development of telecommunication networks, the predictability of network
traffic is of significant interest in network analysis and optimization, bandwidth allocation …

[PDF][PDF] Applying machine learning approaches for network traffic forecasting

S Prajam, C Wechtaisong, AA Khan - Indian Journal of Computer Science …, 2022 - ijcse.com
In the era of the digital world. The communication and the use the internet is an important
role in today's society. As a result, the number of users networks traffic increases but not …

A Systematic and Comprehensive Study on Machine Learning and Deep Learning Models in Web Traffic Prediction

J Trivedi, M Shah - Archives of Computational Methods in Engineering, 2024 - Springer
The practice of predicting the traffic that is headed toward a specific website is known as
web traffic prediction. To govern a network, network traffic forecasting is crucial. Since clients …

A novel traffic prediction method using machine learning for energy efficiency in service provider networks

F Rau, I Soto, D Zabala-Blanco, C Azurdia-Meza, M Ijaz… - Sensors, 2023 - mdpi.com
This paper presents a systematic approach for solving complex prediction problems with a
focus on energy efficiency. The approach involves using neural networks, specifically …

[PDF][PDF] The use of the Kolmogorov-Wiener filter for prediction of heavy-tail stationary processes.

V Gorev, A Gusev, V Korniienko - IntelITSIS, 2022 - ceur-ws.org
We investigate the possibility of the practical use of the Kolmogorov–Wiener filter for the
prediction of a heavy-tail stationary random process. A discrete process and a discrete filter …

[PDF][PDF] The effect of hyperparameter optimization on the estimation of performance metrics in network traffic prediction using the gradient boosting machine model

J Mbelwa, J Agbinya, M Mwita, A Sam - 2023 - 41.59.85.213
Information and Communication Technology (ICT) has changed the way we communicate
and access information, resulting in the high generation of heterogeneous data. The amount …

A multivariate approach for spatiotemporal mobile data traffic prediction

BS Shawel, E Mare, TT Debella, S Pollin… - Engineering …, 2022 - mdpi.com
Widespread deployment of spectrally efficient mobile networks, advancements in mobile
devices, and proliferation of attractive applications has led to an exponential increase in …

Network traffic prediction using online-sequential extreme learning machine

F Rau, I Soto, P Adasme… - 2021 Third South …, 2021 - ieeexplore.ieee.org
For years, it has been a great challenge for Internet Service Providers (ISP) to predict traffic
load or future demand, since each bit of traffic is an economic cost to operators. Additionally …

Forescating mobile network traffic based on deep learning networks

F Rau, I Soto, D Zabala-Blanco - 2021 IEEE Latin-American …, 2021 - ieeexplore.ieee.org
As Internet Service Providers (ISPs) integrate the fifth generation (5G) technology standard
for cellular broadband systems, they may face bursts of network traffic due to the future …

Forecasting telecommunication network states on the basis of log patterns analysis and knowledge graphs modeling

K Krinkin, AI Vodyaho, I Kulikov… - International Journal of …, 2022 - igi-global.com
The article proposes a state forecasting method for telecommunications networks (TN) that is
based on the analysis of behavioral models observed on users' network devices. The …